Selection of machine-readable link type

ABSTRACT

Examples disclosed herein relate to selection of machine-readable link type. Examples include acquisition of an electronic document, selection of a machine-readable link type for evaluation, and a decision of whether at least one characteristic of the document satisfies at least one evaluation metric for use of the selected type of machine-readable link.

BACKGROUND

Various types of machine-readable links, such as one- or two-dimensionalbarcodes, digital watermarks, image fingerprints, and the like, may beoptically readable by a computing device with an image capture device.Such machine-readable links may be encoded or associated with varioustypes of information. In some examples, a machine-readable link may beencoded or associated with information identifying content accessibleover a computer network.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description references the drawings, wherein:

FIG. 1 is a block diagram of an example computing device to select oneof an overt type and a covert type of machine-readable link based on adocument type;

FIG. 2 is a flowchart of an example method for determining a type ofmachine-readable link to use in producing a linked version of anelectronic document;

FIG. 3A is a block diagram of an example computing environment includingan example system to prioritize, based on a selection parameter, atleast one of a plurality of different types of machine-readable linkavailable to be utilized with a document;

FIG. 3B is a block diagram of an example computing environment includingan example system to decide, based on at least one characteristic of thecontent of a document, whether the document satisfies at least oneevaluation metric for use of a selected type of machine-readable link;and

FIG. 4 is a flowchart of an example method for making available, to adestination printing device, a linked version of a document.

DETAILED DESCRIPTION

As noted above, a machine-readable link may be encoded or associatedwith information identifying content accessible over a computer network.For example, a computing device may optically capture themachine-readable link having with an image capture device (e.g., adigital camera, or the like) and then communicate with a linking serviceto access content (e.g., a video, a website, etc.) associated with themachine-readable link by the linking service.

As noted above, there are various types of machine-readable links, suchas, for example, one- and two-dimensional barcodes, digital watermarks,image fingerprints, and the like. In some examples, a link creator maymanually select which of the various types of machine-readable link touse with a particular document. However, such selection processes may becumbersome, or may inhibit automated workflows.

To address these issues, examples described herein include automateddetermination of an appropriate type of machine-readable link to usewith a given document based on characteristic(s) of the document.Examples described herein may acquire a document in an electronicformat, select one of an overt type and a covert type ofmachine-readable link for evaluation based on whether the document is atextual-type document or an image-type document, and decide whether thedocument satisfies at least one evaluation metric for use of theselected type of machine-readable link based on at least onecharacteristic of the content of the document. Such examples may furtherdetermine to produce a first linked version of the document using amachine-readable link of the selected type embodied in the first linkedversion based on the document satisfying the at least one evaluationmetric, and may determine to produce a second linked version of thedocument using a machine-readable link of the non-selected type embodiedin the second linked version based at least in part on the document notsatisfying the at least one evaluation metric.

In this manner, examples described herein may utilize various documentcharacteristics, such as document type and characteristics of thecontent of the document, to determine an appropriate type ofmachine-readable link to use with a given document to produce a linkedversion of the document. In such examples, the linked version may beproduced using a machine-readable link of the determined type embodiedin the linked version of the document and such that associated payoffcontent is accessible through a linking service via optically capturingat least a portion of the linked version.

Referring now to the drawings, FIG. 1 is a block diagram of an examplecomputing device 100 to select one of an overt type and a covert type ofmachine-readable link based on a document type. In the example of FIG.1, computing device 100 includes a processing resource 110 and amachine-readable storage medium 120 comprising (e.g., encoded with)instructions 121-125 executable by processing resource 110. In someexamples, storage medium 120 may include additional instructions. Inother examples, the functionalities described herein in relation toinstructions 121-125, and any additional instructions described hereinin relation to storage medium 120, may be implemented as enginescomprising any combination of hardware and programming to implement thefunctionalities of the engines, as described below.

As used herein, a “computing device” may be a desktop computer, laptop(or notebook) computer, workstation, tablet computer, mobile phone,smart device, server, blade enclosure, or any other processing device orequipment. In examples described herein, a processing resource mayinclude, for example, one processor or multiple processors included in asingle computing device or distributed across multiple computingdevices. In the example of FIG. 1, computing device 100 includes anetwork interface device 130.

For ease of understanding, examples of automated determination of anappropriate type of machine-readable link to use with a given documentbased on characteristic(s) of the document will be described herein inrelation to FIGS. 1 and 2. FIG. 2 is a flowchart of an example method200 for determining a type of machine-readable link to use in producinga linked version of an electronic document. However, in some examples,computing device 100 of FIG. 1 may perform other methods different thanthe method 200 of FIG. 2 or a subset of method 200, and method 200 ofFIG. 2 may be performed by computing device(s) or system(s) other thancomputing device 100 of FIG. 1. Examples described in relation to FIGS.1 and 2 may perform automated determination of an appropriate type ofmachine-readable link to use with a particular document, among aplurality of types of machine-readable link including barcodes, digitalwatermarks, and image fingerprints.

In examples described herein, a “machine-readable link” (or “opticallymachine-readable link”) may be an image associated with a linkingservice that is optically readable by a computing device using an imagecapture device (e.g., a digital camera, or the like) to determinepayload information with which the computing device may obtain access toa digital content payoff assigned to the image in the linking service.Example types of machine-readable links include barcodes (e.g., aone-dimensional barcode, two-dimensional barcode, matrix barcode, QUICKRESPONSE CODE (QR CODE), or the like), digital watermarks, imagefingerprints, and the like. In some examples, each type ofmachine-readable link in a document may be resolved (e.g., the payloadinformation may be determined therefrom) without comparison of thedocument to any other version of the document.

In the example of FIG. 1, instructions 121 may actively acquire (e.g.,retrieve, etc.) or passively acquire (e.g., receive, etc.) a document170 in an electronic format via network interface device 130 ofcomputing device 100 (see 205 of method 200). In such examples, theinstructions 121 may acquire document 170 from network interface device130 directly, or indirectly (e.g., via one or more interveningcomponents, services, processes, or the like, or a combination thereof).

At 210 of method 200, instructions 122 may determine whether document170 is a textual-type document or an image-type document. In examplesdescribed herein, a “textual-type document” is a type of electronicdocument readily utilized for conveying and manipulating text. In someexamples described herein, a system or computing device may define whichtypes of documents are to be considered textual-type documents bymaintaining a list of file formats for such documents (e.g., a wordprocessing format, a spreadsheet file format, portable document format(PDF), etc.), where documents in those file formats are to be consideredtextual-type documents. In examples described herein, an “image-typedocument” is a type of electronic document readily utilized forconveying and manipulating images. In some examples described herein, asystem or computing device may define which types of documents are to beconsidered image-type documents by maintaining a list of file formatsfor such documents (e.g., JPEG, PNG, TIFF, etc.), where documents inthose file formats are to be considered textual-type documents.

In such examples, instructions 122 may determine whether document 170 isa textual-type document or an image-type document based on the fileformat of document 170. For example, instructions 122 may determine thefile format of document 170 in any suitable manner (e.g., based on thefile extension, file signature (or magic number) at the beginning of thedocument, or the like), and then determine the document type based on acomparison of the document type with at least one of a file format listfor textual-type documents and a file format list for image-typedocuments. In such examples, instructions 122 may determine thatdocument 170 is a textual-type document if the file format is at leastone of in the list of textual-type file formats and not in the list ofimage-type file formats, and may determine that document 170 is animage-type document if the file format is at least one of in the list ofimage-type file formats and not in the list of textual-type fileformats.

Instructions 122 may select one of an overt type and a covert type ofmachine-readable link for evaluation based at least in part on whetherdocument 170 is a textual-type document or an image-type document. Insome examples, the selection may comprise a selection of evaluationmetric(s) for a particular type of machine-readable link to compareagainst characteristics of the content of document 170. In examplesdescribed herein, an “overt type” of machine-readable link is a type ofmachine-readable link that is readily observable by the naked eye.Examples of overt types of machine-readable link include barcodes, suchas one-dimensional barcodes, two-dimensional barcodes, matrix barcodes,QR CODES, and the like. In examples described herein, a “covert type” ofmachine-readable link is a type of machine-readable link that is notreadily observable by the naked eye. Examples of covert types ofmachine-readable link include digital watermarks, image fingerprints,and the like.

Instructions 123 may determine characteristics of the content ofdocument 170. In some examples, the particular characteristicsdetermined may depend on the which type of machine-readable link wasselected. For example, the selected type is a digital watermark,instructions 123 may determine a tonal distribution for the content ofdocument 170, as described in more detail below. In examples describedherein, the “content” of a document may include data to be displayedwhen the file is opened with an appropriate viewing or editing computerapplication, and may exclude metadata for the document (e.g., fileextension, header information, magic number, attributes, etc.).

After the selection, instructions 124 may decide whether the determinedcharacteristics of document 170 satisfy at least one evaluation metricfor use of the selected type of machine-readable link. If so, then basedon the satisfaction of the at least one evaluation metric, instructions125 may determine to produce a linked version of document using amachine-readable link of the selected type embodied in the linkedversion of the document such that associated payoff content isaccessible via optically capturing at least a portion of the linkedversion of the document. If not, then based at least in part on thenon-satisfaction of the at least one evaluation metric, instructions 125may determine to produce a linked version of the document using amachine-readable link of the non-selected type embodied in the linkedversion of the document such that associated payoff content isaccessible via optically capturing at least a portion of the secondversion of the document.

Referring to FIGS. 1 and 2, in some examples, at 210 of method 200,instructions 122 may determine that document 170 is a textual-typedocument and, based on that determination, may select an overt type ofmachine-readable link for evaluation, such as any type of barcode (see215 of method 200). In such examples, at 220 of method 200, instructions123 may determine characteristics of the content of document 170relevant to use of a barcode, and instructions 124 may decide whetherthe characteristics satisfy at least one evaluation metric for use ofthe selected type of machine-readable link (i.e., a barcode). In someexamples, the characteristic(s) may include the respective dimensions ofarea(s) of white space in margins (or borders) of the content ofdocument 170. In such examples, an evaluation metric for barcodes mayinclude target dimensions for a barcode, wherein the evaluation metricis satisfied when the margin(s) of document 170 include at least onearea of white space having respective dimensions (e.g., height andwidth) at least as large as respective target dimensions (e.g., heightand width) for a barcode. In such examples, the target dimensions may bepredefined by computing device 100. As an example, the target dimensionsmay be a height of 100 pixels and a width of 100 pixels. In otherexamples, any other suitable target dimensions may be used (e.g.,105×105 pixels, etc.).

In such examples, instructions 123 may identify the margins of thecontent of document 170 using any suitable page frame detectiontechnique. Instructions 124 may then determine whether, for any area ofwhite space in the margins of the content, the dimensions of the areaare at least as large as the target dimensions for a barcode. In someexamples, when that is determined to be true, instructions 124 maydetermine that the characteristics of the content of document 170satisfy the evaluation metric for barcodes.

In some examples, the characteristics of the content of document 170 mayalso include the skew angle of the content of document 170. In suchexamples, an additional evaluation metric for a barcode may include askew angle threshold above which barcodes may not be used, and which issatisfied by a document having content with a determined skew angle lessthan the threshold. In such examples, instructions 123 may determine theskew angle of document content with any suitable technique. In someexamples, instructions 124 may determine that the evaluation metrics foruse of the barcode are satisfied based on a determining that both theskew angle and target dimension metrics are satisfied.

Based on the satisfaction of the barcode evaluation metric(s) by thecharacteristics of the content of document 170, at 225 of method 200,instructions 125 may determine to produce a linked version of thedocument comprising a barcode (i.e., the selected type ofmachine-readable link) such that associated payoff content is accessiblethrough a linking service via optically capturing the barcode in thelinked version.

In examples described herein, a “linking service” may be a serviceimplemented by one or more networked computing devices to create andmanage optically machine-readable links, and to create and manage theassignment of digital content payoffs to respective opticallymachine-readable links. In some examples, a linking service may providea computing device access to a digital content payoff assigned to agiven optically machine-readable link in response to an indication thatthe computing device has captured an image of the given opticallymachine-readable link. In examples described herein, a “content payoff”(or “digital content payoff”) may be any suitable type of informationthat may be accessed (e.g., retrieved, viewed, etc.) over a computernetwork, such as a digital video, a website or webpage, a uniformresource identifier (URI) (such as a uniform resource locator (URL)) forweb content (e.g., a website), or the like.

In some examples, instructions 125 may determine that a linked versionof document 170 be produced with a barcode added to the document, wherethe barcode encodes payload information registered in the linkingservices such that, in response to receiving an indication that acomputing device has captured an image of the barcode (e.g., via receiptof the payload from the computing device), the linking service mayreturn to the computing device any payoff content associated with thebarcode payload information in the linking service. In some examples,payoff content may be associated with a payload when the payload isfirst registered in the linking service. In some examples, the payoffcontent associated with a particular payload may be changed at a latertime, such that the payload is associated with different payoff content.

In some examples, instructions 125 may directly or indirectlycommunicate the determination to produce the linked version includingthe barcode to another system, component, functionality, or the like,(e.g., the linking service) to create the determined linked version fromdocument 170. In some examples. Instructions 125 may further determinean area at which to place the barcode (which may be communicated aswell), the area having dimensions at least as large as the targetdimensions.

In other examples, at 220 of method 200, instructions 124 may determinethat the characteristics of the content of document 170 do not satisfyat least one of the evaluation metric(s) for use of a barcode. Forexample, instructions 124 may determine that a plurality of areas ofwhite space in the margins of the content of document 170 each haverespective dimensions that are smaller (in at least one dimension) thanthe target dimensions. Based on this determination, at 230 of method200, instructions 125 may determine to produce a linked version of thedocument comprising a non-selected type of machine-readable link. Forexample, instructions 125 may determine to produce a linked version ofthe document comprising a digitally watermarked region of greyscale tint(e.g., a watermarked region of grey color) through which associatedpayoff content is accessible through the linking service via opticallycapturing the digitally watermarked region. In some examples,instructions 125 may directly or indirectly communicate thedetermination to produce the linked version including the barcode toanother system, component, functionality, or the like, to create thedetermined linked version from document 170.

In examples described herein, digital watermarking refers to anysuitable technique for altering the data of an image (e.g., values ofthe color components of pixels of an image such as RGB values, etc.) toembed a payload in the image such that a computing device may determinethe payload from a captured image (e.g., digital photograph) of thealtered image, but the change to the altered image is not readilyperceptible to the naked eye.

Returning to 210 of method 200, in other examples, instructions 122 mayselect a covert type of machine-readable link for evaluation based atleast in part on the document being an image-type document. In someexamples, instructions 122 may select one of a plurality of covert typesof machine-readable link based on document 170 being an image-typedocument and based on whether the content of document 170 satisfies aresolution evaluation metric (see 235 of method 200). In such examples,instructions 122 may determine a resolution of the content of document170 and determine whether the resolution satisfies the resolutionevaluation metric, which may be a resolution threshold. For example, theresolution threshold may indicate a target resolution below whichdigital watermarking may not be selected. In such examples, instructions122 may determine that the content of document 170 satisfies theresolution evaluation metric when the determined resolution is greaterthan or equal to the resolution threshold, and may determine that thecontent of document 170 does not satisfy the resolution evaluationmetric when the determined resolution is less than the resolutionthreshold. In some examples, the resolution threshold may be 72 dots perinch (DPI), or another suitable resolution.

In some examples, instructions 122 may determine, at 210 of method 200,that document 170 is an image-type document and may determine, at 235 ofmethod 200, that the resolution of the content of document 170 satisfiesthe resolution evaluation metric. Based on those determinations,instructions 122 may select digital watermarking for evaluation (240 ofmethod 200). In such examples, at 245 of method 200, instructions 123may determine characteristics of the content of document 170 that arerelevant to digital watermarking, including a tonal distribution for thecontent of document 170, and instructions 124 may decide whether thedetermined characteristics satisfy watermarking evaluation metric(s) foruse of digital watermarking.

The tonal distribution determined by instructions 123 may includeinformation identifying, for each brightness value in the tonal range ofthe content, the number of pixels of the content having that brightnessvalue, which instructions 123 may determine from the content of document170.

In such examples, the watermarking evaluation metrics may relate to thetonal distribution of the content. For example, the tonal range of thecontent may be partitioned into a lower range “L” including the lowest20% of the tonal range, a middle range “M” including the middle 60% ofthe tonal range, and an upper range “U” including the highest 20% of thetonal range, where the lower, middle, and upper ranges arenon-overlapping, and the middle range is between the upper and lowerranges. In such examples, a first watermarking metric may be based onthe distribution of the pixels between the different ranges. Forexample, whether the number of pixels in middle range M (represented as“p(M)”) is greater than the number of pixels in the upper range(represented as “p(U)”) and the number of pixels in the lower range(represented as “p(L)”) combined (i.e., whether p(M)>p(L)+p(U)).Instructions 124 may decide that the first watermarking metric issatisfied when the determined tonal distribution for the content ofdocument 170 satisfies this relationship, and otherwise not.

A second watermarking metric may be, for example, whether more than 80%of the pixels in the content are distributed across at least 30% of thedifferent values in the tonal range. Instructions 124 may decide thatthe second watermarking metric is satisfied when the determined tonaldistribution for the content of document 170 satisfies thisrelationship, and otherwise not.

In such examples, instructions 124 may decide that the characteristicsof the content of document 170 satisfy the watermarking evaluationmetric(s) for the use of digital watermarking when instructions 124decide that at least the first and second watermarking evaluationmetrics are satisfied. In other examples, instructions 124 may decidethat the characteristics of the content of document 170 satisfy thewatermarking evaluation metric(s) for the use of digital watermarkingwhen instructions 124 decide that at least the first watermarkingevaluation metric is satisfied.

Based on instructions 124 deciding that the watermarking evaluationmetrics are satisfied as described above, then at 230 of method 200,instructions 125 may determine to produce a linked version of thedocument using a digital watermark embodied in the linked version suchthat associated payoff content is accessible via optically capturing atleast the portion of the linked version of the document including thedigital watermark. In some examples, based on instructions 124 decidingthat the watermarking evaluation metrics are not satisfied as describedabove (see 250 of method 200), then instructions 123 and 124 may proceedto 260 to determine whether fingerprinting evaluation metric(s) aresatisfied, as described below, for use of an image fingerprint (i.e., anon-selected type) if so, and if not may proceed to 220 to determinewhether barcode evaluation metric(s) are satisfied, as described above,for use of a barcode (i.e., a non-selected type) if so.

In other examples, image fingerprinting may be the selected forevaluation. In examples described herein, image fingerprinting is atechnique for generating an “image fingerprint” comprising informationrepresenting characteristic aspects of the image, such as featuresdepicted in the image (e.g., object(s) or portions thereof), color(s),texture(s), noise, correlations between features of the image, or thelike, or a combination thereof. In such examples, an image fingerprintmay be generated based on the original image (document) itself, withoutmodification. When utilizing an image fingerprint type machine-readablelink, an image fingerprint is generated to represent the image. Thisimage fingerprint may be unique to the image, or otherwise distinctlyrepresent the image such that it is different than image fingerprintsfor at least a large number of different images. Since the imagefingerprint represents (and may be generated from) the content of theimage, the image fingerprint is embodied in the image.

When used as a machine-readable link for a document, an imagefingerprint may be generated from the image and registered in a linkingservice, as described above, such that the linking service, in responseto receiving an indication that a computing device has captured an imageof the document content (e.g., via receipt of the image or the imagefingerprint generated from the image from the computing device), mayreturn to the computing device any payoff content associated with theimage fingerprint in the linking service. In such examples, thecomputing device may generate the image fingerprint from the capturedimage, or the linking service may generate the fingerprint from theimage received from the computing device.

Referring again to FIGS. 1 and 2, in some examples, instructions 122 maydetermine, at 210 of method 200, that document 170 is an image-typedocument and may determine, at 235 of method 200, that the resolution ofthe content of document 170 does not satisfy the resolution evaluationmetric. Based on those determinations, instructions 122 may select imagefingerprinting for evaluation (255 of method 200).

In such examples, at 260 of method 200, instructions 123 may determinecharacteristics of the content of document 170 that are relevant toimage fingerprinting, including a number of features represented in theimage of document 170, and instructions 124 may decide whether thedetermined characteristics satisfy fingerprinting evaluation metric(s)for use of image fingerprinting.

For example, instructions 123 may determine a number of features thatcan be identified in the image using any suitable technique. In someexamples, instructions 123 may determine how many features can beidentified in the image using a scale-invariant feature transform (SIFT)technique. In such examples, a fingerprinting evaluation metric mayinclude a threshold number of features identified from content of adocument. In such examples, the fingerprinting evaluation metric may besatisfied when at least the threshold number of features are identifiedin the content of the document. In some examples, the threshold may be apre-defined or default value specified by computing device 100. In otherexamples, the threshold may be a configurable value (e.g., a parameterspecified by a user, etc.).

In such examples, instructions 123 may determine characteristics of thecontent of document 170, including the number of identifiable featuresin the content, and instructions 124 may decide that fingerprintingevaluation metric(s) are satisfied when at least the number of featuresidentified in the content is greater than or equal to the thresholdnumber, and may otherwise determine that the fingerprinting evaluationmetric(s) are not satisfied.

Based on instructions 124 deciding that the fingerprinting evaluationmetric(s) are satisfied as described above, then at 270 of method 200,instructions 125 may determine to produce a linked version of thedocument using an image fingerprint embodied in the linked version suchthat associated payoff content is accessible via optically capturing atleast the portion of the linked version of the document embodying theimage fingerprint the digital watermark. In such examples, the linkedversion may be document 170 itself (without modification), with theimage fingerprint generated from the content of document 170 beingregistered in the linking system.

In some examples, based on instructions 124 deciding that the imagefingerprinting evaluation metrics are not satisfied as described above(see 265 of method 200), then instructions 123 and 124 may proceed to245 to determine whether watermarking evaluation metric(s) aresatisfied, as described above, for use of a digital watermark (i.e., anon-selected type) if so, and if not may proceed to 220 to determinewhether barcode evaluation metric(s) are satisfied, as described above,for use of a barcode (i.e., non-selected type) if so.

In examples described herein, different “types” of machine-readable linkmay be types of machine-readable link that are parsed, read, analyzed,or otherwise interpreted to determine payload information in differentways or using different techniques, or the like. For example, barcodes,digital watermarks, and image fingerprints are each different types ofmachine-readable link in examples described herein.

In some examples, an optically machine-readable link, such as a barcode,may comprise the payload information encoded or embedded therein. Insome examples, a machine-readable link such as digital watermark maycomprise the payload information encoded or embedded in a carrier image.In such examples, a computing device using an image capture device maydetermine, acquire, etc., the payload information by decoding, parsing,etc., the link in accordance with the manner in which the information isencoded or embedded in the link. In other examples, a target image maynot contain encoded or embedded payload information. In such examples, acomputing device using an image capture device may determine, acquire,etc., the payload information based on features, characteristics, orother aspects of the target image itself, or the like, or a combinationthereof.

In examples described herein, a “network interface device” may be ahardware device to communicate over at least one computer network. Insome examples, a network interface may be a network interface card (NIC)or the like. As used herein, a computer network may include, forexample, a local area network (LAN), a wireless local area network(WLAN), a virtual private network (VPN), the Internet, or the like, or acombination thereof. In some examples, a computer network may include atelephone network (e.g., a cellular telephone network).

As used herein, a “processor” may be at least one of a centralprocessing unit (CPU), a semiconductor-based microprocessor, a graphicsprocessing unit (GPU), a field-programmable gate array (FPGA) configuredto retrieve and execute instructions, other electronic circuitrysuitable for the retrieval and execution instructions stored on amachine-readable storage medium, or a combination thereof. Processingresource 110 may fetch, decode, and execute instructions stored onstorage medium 120 to perform the functionalities described below. Inother examples, the functionalities of any of the instructions ofstorage medium 120 may be implemented in the form of electroniccircuitry, in the form of executable instructions encoded on amachine-readable storage medium, or a combination thereof.

As used herein, a “machine-readable storage medium” may be anyelectronic, magnetic, optical, or other physical storage apparatus tocontain or store information such as executable instructions, data, andthe like. For example, any machine-readable storage medium describedherein may be any of Random Access Memory (RAM), volatile memory,non-volatile memory, flash memory, a storage drive (e.g., a hard drive),a solid state drive, any type of storage disc (e.g., a compact disc, aDVD, etc.), and the like, or a combination thereof. Further, anymachine-readable storage medium described herein may be non-transitory.In examples described herein, a machine-readable storage medium or mediais part of an article (or article of manufacture). An article or articleof manufacture may refer to any manufactured single component ormultiple components. The storage medium may be located either in thecomputing device executing the machine-readable instructions, or remotefrom but accessible to the computing device (e.g., via a computernetwork) for execution.

In some examples, instructions 121-125 may be part of an installationpackage that, when installed, may be executed by processing resource 110to implement the functionalities described herein in relation toinstructions 121-125. In such examples, storage medium 120 may be aportable medium, such as a CD, DVD, or flash drive, or a memorymaintained by a server from which the installation package can bedownloaded and installed. In other examples, instructions 121-125 may bepart of an application, applications, or component(s) already installedon a computing device 100 including processing resource 110. In suchexamples, the storage medium 120 may include memory such as a harddrive, solid state drive, or the like. In some examples, functionalitiesdescribed herein in relation to FIGS. 1 and 2 may be provided incombination with functionalities described herein in relation to any ofFIGS. 3A-4.

FIG. 3A is a block diagram of an example computing environment 301including an example system 300 to prioritize, based on a selectionparameter 360, at least one of a plurality of different types ofmachine-readable link available to be utilized with a document 170.

System 300 includes at least engines 322-326, which may be anycombination of hardware and programming to implement the functionalitiesof the engines. In examples described herein, such combinations ofhardware and programming may be implemented in a number of differentways. For example, the programming for the engines may be processorexecutable instructions stored on at least one non-transitorymachine-readable storage medium and the hardware for the engines mayinclude at least one processing resource to execute those instructions.In such examples, the at least one machine-readable storage medium maystore instructions that, when executed by the at least one processingresource, implement engines 322-326. In such examples, system 300 mayinclude the at least one machine-readable storage medium storing theinstructions and the at least one processing resource to execute theinstructions, or one or more of the at least one machine-readablestorage medium may be separate from but accessible to system 200 and theat least one processing resource (e.g., via a computer network).

In some examples, the instructions can be part of an installationpackage that, when installed, can be executed by the at least oneprocessing resource to implement at least engines 322-326. In suchexamples, the machine-readable storage medium may be a portable medium,such as a CD, DVD, or flash drive, or a memory maintained by a serverfrom which the installation package can be downloaded and installed. Inother examples, the instructions may be part of an application,applications, or component already installed on system 300 including theprocessing resource. In such examples, the machine-readable storagemedium may include memory such as a hard drive, solid state drive, orthe like. In other examples, the functionalities of any engines ofsystem 300 may be implemented in the form of electronic circuitry.

System 300 also includes a network interface device 330 and a linkingservice 340, which comprises an analytics resource, a linking repository342, and a link engine 326. In the example of FIG. 3A, an acquisitionengine 322 may actively or passively acquire, in at least onecommunication 380, a document 170 in an electronic format and aselection parameter 360 via network interface device 330 of system 300.System 300 may make a plurality of different types of machine-readablelink available to be utilized with document 170, and may implementautomated determination of which of the different types ofmachine-readable link to use with document 170 based on the content ofdocument 170 and the selection parameter 360. In some examples, thedifferent types of machine-readable link may include at least one typeof barcode, digital watermarking, and an image fingerprinting.

In the example of FIG. 3A, selection parameter 360 may specify apreference to guide the automated determination of the type ofmachine-readable link to utilize. A priority engine 323 may prioritizeat least one of the plurality of different types of machine-readablelink available to be utilized with document 170 based on selectionparameter 360. For example, selection parameter 360 may specify apreference to choose a type of machine-readable link based at least inpart on popularity, such as the relative popularity of the plurality ofdifferent types of machine-readable link. In such examples, based onselection parameter 360 specifying a preference to choose based onpopularity, priority engine 323 may access link type popularity data ofan analytics resource 341 of linking service 340 and prioritize the mostpopular of the plurality of types of machine-readable link. For example,analytics resource 341 may maintain popularity data indicating therelative popularity of each of the types of machine-readable link basedon, for example, how much each of the different types ofmachine-readable link are captured (e.g., scanned) for linking service340 to resolve (e.g., and return payoff content). In such examples,engine 323 may determine and prioritize the most scanned type ofmachine-readable link. In some examples, the popularity data may bedetermined based on context (e.g., most popular for a given region,time, type of user, or the like, or a combination thereof).

In examples of selection parameter 360 specifying a popularitypreference, priority engine 323 may prioritize a single type ofmachine-readable link to be selected for evaluation. In other examples,engine 323 may prioritize multiple types of machine-readable link to beselected for evaluation. Also, in some examples, non-prioritized typesof machine-readable link may be evaluated for use when the evaluationmetric(s) for each of the prioritized type(s) are determined not besatisfied. In other examples, the non-prioritized types may beeliminated from consideration such that they are not utilized withdocument 170 even when the evaluation metric(s) for each of theprioritized type(s) are determined not be satisfied.

In some examples, when selection parameter 360 specifies a popularitypreference, priority engine 323 may prioritize a single type ofmachine-readable link to be selected for evaluation, and system maysubsequently evaluate non-prioritized type(s) when the evaluationmetric(s) are not satisfied for the prioritized type. In other examples,based on selection parameter 360 specifying another preference otherthan popularity, priority engine 323 may prioritize multiple of thetypes of machine-readable link and eliminate each non-prioritized typeof machine-readable link from consideration, as described above.

Other preferences that may be specified include, for example,preferences based on monetary cost for use of the type ofmachine-readable link, whether the type of machine-readable link iscovert or overt, whether the type of machine-readable link involves amodification of document 170, etc. For example, a selection parameter360 based on monetary cost may specify a preference that cost bemaintained below a given cost threshold. In some examples, when the costof two-dimensional barcodes and image fingerprints are below thethreshold, but the cost of digital watermarks is above the threshold,engine 323 may prioritize two-dimensional barcodes and imagefingerprints, and eliminate digital watermarks from consideration. Inanother example, when a selection parameter 360 specifies a preferencethat covert types of machine-readable link not be used, engine 323 mayprioritize digital watermarks and image fingerprints, and eliminatebarcodes.

In the example of FIG. 3A, selection engine 324 may select one of theprioritized type(s) of machine-readable link for evaluation. In examplesin which there is one prioritized type of machine-readable link, thattype may be selected for evaluation. In examples in which multiple typesare prioritized, engine 324 may select among the prioritized types onthe bases described above in relation to FIGS. 1 and 2. For example,when overt and covert types of machine-readable link are among theprioritized types, engine 324 may determine whether document 170 is atextual-type document or an image-type document, and may select betweenthe overt and covert types on that basis, as described above. In otherexamples, when digital watermarking and image fingerprinting are amongthe prioritized types, engine 324 may select between them based on imageresolution, as described above.

A characteristic engine 325 may determine at least one characteristic ofthe content of document 170 and may decide whether the at least onecharacteristic satisfies at least one evaluation metric for use of theselected type of machine-readable link, as described above in relationto instructions 123 and 124 of FIG. 1. Based on the decision of whetherthe characteristic(s) satisfy the evaluation metric(s), characteristicengine 325 may instruct link engine 326 to produce a linked version ofdocument 170 using the selected type of machine-readable link.

For example, when the selected type is an overt type of machine-readablelink, such as a type of barcode, characteristic engine 325 may instructlink engine 326 to produce a linked version of document 170 includingthe overt type of machine-readable link when the characteristic(s)satisfy the metric(s) for the overt type of machine-readable link. Inresponse (i.e., based on the selected type being the over type and thecharacteristic(s) satisfying the metric(s)), link engine 326 may createa linked version 372 of document 170 comprising an instance of the overttype of machine-readable link 350 through which associated payoffcontent 355 is accessible via optically capturing machine-readable link350 (e.g., with computing device 392). In such examples, link engine 326may create an instance of the overt machine-readable link which encodesa payload 352 and may create the linked version 372 of the document byadding the created instance of the link 350 to the original document 170and registering the payload 352 in inking repository 342 such that itmay be associated with a content payoff 355.

In such examples, a computing device 392 remote from linking service 340(e.g., remote from at least system 300) may capture (e.g., with an imagecapture device such as a digital camera or the like) an image of theinstance of machine-readable link 350 from a physical (e.g., printed)copy of linked version 372. From the captured image, the computingdevice 392 may determine the payload 352 of link 350 (e.g., usingmachine-readable instructions executable to implement a readerapplication). In such examples, the computing device may provide anindication 382 that the computing device has captured an image ofmachine-readable link 350, which may include the payload 352 determinedfrom link 350.

In response to indication 382, linking service 340 may determine thecontent payoff 355 assigned to payload 352 and provide computing device392 access 384 to the content payoff 355. In examples described herein,a linking service may provide a computing device access to a digitalcontent payoff by providing a copy of the digital content (e.g., adigital video file), by enabling the computing device to view, download,etc., a remote copy of the content (e.g., a digital video file storedremotely), by directing (or redirecting) the computing device to thecontent (e.g., directing a browser of the computing device to a URL thatis the payoff), or in any other suitable manner.

In other examples, when the selected type is digital watermarking,characteristic engine 325 may instruct link engine 326 to produce alinked version of document 170 including a digital watermark when thecharacteristic(s) satisfy the metric(s) for the digital watermark. Inresponse (i.e., based on digital watermarking being the selected typeand the characteristic(s) satisfying the metric(s)), link engine 326 maycreate a linked version 372 of document 170 comprising a digitalwatermark 350 encoding a payload 352 such that associated payoff content355 is accessible through linking service 340 via optically capturingthe portion of linked version comprising the digital watermark 350(e.g., with a computing device 392). In such examples, link engine 326may modify document 170 to add the digital watermark 350 to it andregister the payload 352 in linking repository 342 such that it may beassociated with a content payoff 355, to thereby create the linkedversion 372.

In other examples, when the selected type is image fingerprinting,characteristic engine 325 may instruct link engine 326 to produce alinked version of document 170 having an image fingerprint 350 embodiedtherein when the characteristic(s) satisfy the metric(s) for the imagefingerprint. In response (i.e., based on image fingerprinting being theselected type and the characteristic(s) satisfying the metric(s)), linkengine 326 may create the linked version 372 by registering (e.g.,linking) image fingerprint information 352 embodied by an imagefingerprint 350 of document 170 in linking service 340 such thatassociated payoff content is accessible through the linking service viaoptically capturing an image of document 170 (e.g., with a computingdevice 392). In such examples, the linked version 372 is the same as theoriginal document 170. In such examples, link engine 326 create thelinked version 372 via the registering of the image fingerprint data andwithout modifying document 170.

As noted above, in some examples, non-prioritized types ofmachine-readable link are not eliminated. In such examples, based inpart on the document not satisfying the at least one evaluation metricfor the selected type, characteristic engine 325 may decide whether atleast one characteristic of the content of the document satisfies atleast one other evaluation metric for use of a non-prioritized type ofmachine-readable link. In such examples, based at least in part on thecharacteristic(s) satisfying the other evaluation metric(s) (i.e., inresponse to instruction from engine 325 on that basis), link engine 326may create the linked version of document 170 using a machine-readablelink of the non-prioritized type embodied in linked version 372 and suchthat associated payoff content 355 is accessible through linking service340 via optically capturing at least a portion of the linked version ofdocument 170.

In examples described herein, engines 322-325 may be implemented in thesame computing device as at least a portion of linking service 340. Inother examples, engines 322-325 and linking service 340 each may beimplemented in computing device(s) separate but accessible to oneanother (e.g., via a computer network.) In some examples,functionalities described herein in relation to FIG. 3A may be providedin combination with functionalities described herein in relation to anyof FIGS. 1-2 and 38-4.

FIG. 3B is a block diagram of an example computing environment 302including an example system to decide, based on at least onecharacteristic of the content of a document, whether the documentsatisfies at least one evaluation metric for use of a selected type ofmachine-readable link. In the example of FIG. 3B, computing environment302 includes a system 310 including a linking service 340, as describedabove in relation to FIG. 3A, a decision service 320, and a remoteprinting service 315. Decision service 320 includes engines 322-325,described above in relation to FIG. 3A. Components of FIG. 3B describedabove in relation to FIG. 3A may perform each of the functionalitiesdescribed above in relation to FIG. 3A.

In examples described herein, a “remote printing service” may be aservice implemented by one or more networked computing devices toreceive, from a sending computing device, a message requesting thatspecified print content be printed at a destination printing device, andto make the specified print content available to the destinationprinting device a print-ready format, wherein the sending computingdevice and the printing device are each remote from the networkedcomputing device(s) implementing the remote printing service. Inexamples described herein, a remote printing service may receivemessages requesting printing from any of a plurality of differentsending computing devices, and may make print content available to anyof a plurality of different destination printing devices. In someexamples, a message requesting printing may include the print content ormay otherwise indicate (e.g., provide a reference to) the print content.In some examples, a message requesting printing may be an email message.In examples described herein, first device “remote” from a second devicemay be a first device that is separate from, and not directly connectedto, the second device, wherein the first and second devices may accessone another over a computer network.

In the example of FIG. 3B, remote printing service 315 is incommunication with at least one destination printing device 390, as wellas decision service 320 and linking service 340. In examples describedherein, a “printing device” may be a hardware device, such as a printer,multifunction printer (MFP), three-dimensional (3D) printer, or anyother device including at least functionalities to physically producegraphical representation(s) (e.g., text, images, etc.) on paper, othermedia, or the like. In some examples, an MFP may be capable ofperforming a combination of multiple different functionalities such as,for example, printing, photocopying, scanning, faxing, etc. In examplesdescribed herein, a printing device may be capable of communicating overa computer network, such as the internet, or the like. Such a printingdevice may be referred to herein as a “web-connected” printing device.

In the example of FIG. 3B, remote printing service 315 comprises anetwork interface device 316, a message engine 317, and a print engine318. Each of engines 317 and 318 may be implemented as enginescomprising any combination of hardware and programming to implement thefunctionalities of the engines, as described above. In some examples,services 315, 320, and 340 may be implemented, at least in part, on thesame computing device. In other examples, services 315, 320, and 340 mayeach be implemented on computing device(s) separate from one another butin communication via at least one computer network. In the example ofFIG. 3B, computing environment 302 may also include storage 395, whichmay be included in system 300 or remote from but accessible to system300 (e.g., via a computer network). Storage 395 may be implemented by atleast one machine-readable storage medium.

Operations of computing environment 302 of FIG. 3B will be describedherein in relation to method 400 of FIG. 4. However, in some examples,system 310 of FIG. 3B may perform other methods different than method400 of FIG. 4 or a subset of method 400, and method 400 of FIG. 4 may beperformed by computing device(s) or system(s) other than system 310.

FIG. 4 is a flowchart of an example method 400 for making available, toa destination printing device, a linked version of a document. At 405 ofmethod 400, message engine 317 of remote printing service 315 mayactively or passively acquire, from a computer network and with networkinterface device 316, a message 305 requesting that an electronicdocument 170 included in message be printed. In some examples, themessage 305 may specify a destination printing device 390 at which toprint document 170. In some examples, message 305 may be an emailmessage including document 170 in any suitable manner (e.g., as anattachment) and addressed to an email address assigned to destinationprinting device 390 in remote printing service 315. In such examples,this destination address may indicate, to remote printing service 315,that message 305 is a request to print. In other examples, message 305may be any other suitable type of message, such as an applicationprogramming interface (API) function call.

Message engine 317 may provide document 170 to acquisition engine 322 ofdecision service 320 for automated determination of a type ofmachine-readable link to use with document 170. At 410 of method 400,selection engine 324 may select one of an overt type and a covert typeof machine-readable link based on whether document 170 is a textual-typedocument or an image-type document. In some examples, prior toselection, priority engine 323 may prioritize at least one type ofmachine-readable link based on a selection parameter, as describedabove.

At 415, characteristic engine 325 may decide whether characteristics ofthe content of document 170 satisfy evaluation metric(s) for use of theselected type of machine-readable link, as described above. Based on thecharacteristic(s) satisfying the metric(s), at 420, link engine 326 mayproducing a linked version of document 170 using a machine-readable linkof the selected type embodied in the linked version such that associatedpayoff content 355 is accessible to a computing device 392 throughlinking service 340 via optically capturing at least a portion of thelinked version, as described above.

For example, when the selected type is an overt type of machine-readablelink or digital watermarking, producing the linked version 372 mayinclude adding the selected type of machine-readable link to theacquired electronic document to create the linked version 372 ofdocument 170, as described above. In other examples, the linked version372 may be created with an image fingerprint embodied therein, asdescribed above.

In other examples, based at least in part on the characteristic(s) notsatisfying the metric(s), at 425 link engine 326 may produce a secondlinked version of document 170 using a machine-readable link of thenon-selected type embodied in the second linked version. For example,when the selected type is a covert type machine-readable link and themetric(s) are not satisfied, producing the linked version with thenon-selected type includes engine 325 determining whether othercharacteristics of the content satisfy a watermarking evaluation metric.If so, then engine 326 may produce the second linked version with adigital watermark as described above. If not, then engine 325 maydetermine whether still other (i.e., different) characteristics satisfya fingerprinting evaluation metric. Based in part on the differentcharacteristics satisfying the fingerprinting evaluation metric, linkengine 326 may link the acquired electronic document 170 in linkingservice 340 via an image fingerprint of the acquired electronicdocument, by, for example, registering image fingerprint information forthe document in linking repository 342, as described above. In suchexamples, the second linked version is the same as the acquiredelectronic document 170.

At 430 of method 400, print engine 318 may make available, todestination printing device 390 via a computer network, the producedfirst or second linked version of document 170 in a print-ready format386 for destination printing device 390. In some examples, print engine318 may acquire the linked version from link engine 326 and convert(e.g., render) the linked version into the print-ready format, if it isnot acquired in the print-ready format

In some examples, remote printing service 315, in response to message305, may store a copy of document 170 in storage 395. In such examples,the content payoff 355 may be a reference (e.g., address, etc.) to thedocument 170 stored in storage 395. In such examples, after destinationprinting device 390 prints linked version 372 including machine-readablelink 350, by capturing an image of at least a portion of the linkedversion 372, computing device 392 may obtain access to content payoff355 through which it may access the stored electronic version ofdocument 170 in storage 390. In such examples, system 300 may select,without user intervention, a suitable type of machine-readable link withwhich to link a printed version of a document 170 to a stored electronicversion of the document 170.

Although the flowchart of FIG. 4 shows a specific order of performanceof certain functionalities, method 400 is not limited to that order. Forexample, the functionalities shown in succession in the flowchart may beperformed in a different order, may be executed concurrently or withpartial concurrence, or a combination thereof. In some examples,functionalities described herein in relation to FIG. 4 may be providedin combination with functionalities described herein in relation to anyof FIGS. 1-3B. All of the features disclosed in this specification(including any accompanying claims, abstract and drawings), and/or allof the steps of any method or process so disclosed, may be combined inany combination, except combinations where at least some of suchfeatures and/or steps are mutually exclusive.

What is claimed is:
 1. An article comprising at least one non-transitorymachine-readable storage medium comprising instructions executable by aprocessing resource of a computing device to: acquire, via a networkinterface device, a document in an electronic format; select, basedwhether the document is a textual-type or an image-type document, one ofan overt type and a covert type of machine-readable link for evaluation;determine, with the computing device, characteristics of the content ofthe document, including a tonal distribution for the content when theselected type is a digital watermark; decide whether the characteristicssatisfy an evaluation metric for use of the selected type ofmachine-readable link; based on satisfaction of the evaluation metric,determine to produce a first linked version of the document using amachine-readable link of the selected type embodied in the first linkedversion; and based at least in part on non-satisfaction of the least oneevaluation metric, determine to produce a second linked version of thedocument using a machine-readable link of the non-selected type embodiedin the second linked version.
 2. The storage medium of claim 1, whereinthe instructions to select comprise instructions to: select the overttype of machine-readable link for evaluation based on the document beinga textual-type document.
 3. The storage medium of claim 2, wherein: theinstructions to decide comprise instructions to determine whetherdimensions of an area of white space in a margin of the content of thedocument are at least as large as target dimensions for a barcode, whenthe selected type is a barcode; and the instructions to determine toproduce the first linked version comprise instructions to determine toproduce a first linked version of the document comprising a barcode at adetermined area of the document and through which associated payoffcontent is accessible through a linking service via optically capturingthe barcode in the first linked version.
 4. The storage medium of claim3, wherein the instructions to determine to produce the second linkedversion comprise instructions to: based on the respective dimensions ofareas of white space in the margins of the content of the document beingsmaller than the target dimensions, determine to produce the secondlinked version of the document comprising a digitally watermarked regionof greyscale tint through which associated payoff content is accessiblethrough the linking service via optically capturing the digitallywatermarked region.
 5. The storage medium of claim 1, wherein theinstructions to select comprise instructions to: select the covert typeof machine-readable link for evaluation based at least in part on thedocument being an image-type document.
 6. The storage medium of claim 5,wherein: the instructions to select comprise instructions to: determinewhether the content of the document satisfies a resolution evaluationmetric; and the instructions to decide comprise instructions to: basedon the document satisfying the resolution evaluation metric, determinewhether the characteristics of the content satisfy a watermarkingevaluation metric; and based on the document not satisfying theresolution evaluation metric, determine whether the characteristics ofthe content satisfy a fingerprinting evaluation metric, wherein thefirst version is the acquired electronic document when the imagefingerprinting evaluation metric is satisfied.
 7. A system comprising:an acquisition engine to acquire a document in an electronic format anda selection parameter; a priority engine to prioritize, based on theselection parameter, at least one of a plurality of different types ofmachine-readable link available to be utilized with the document; aselection engine to select one of the at least one prioritized type ofmachine-readable link for evaluation, wherein the selection is based atleast in part on whether the document is a textual-type or an image-typedocument when overt and covert types of machine-readable link are amongthe prioritized types of machine-readable link; and a characteristicengine to decide whether at least one characteristic of the content ofthe document satisfies at least one evaluation metric for use of theselected type of machine-readable link; and a link engine to, based onthe at least one characteristic satisfying the at least one evaluationmetric and the selected type being the overt type of machine-readablelink, create a linked version of the document comprising the overt typeof machine-readable link through which associated payoff content isaccessible via optically capturing the overt type of machine-readablelink.
 8. The system of claim 7, wherein the link engine is further to,based on the at least one characteristic satisfying the at least oneevaluation metric and the selected type being a digital watermark,create the linked version of the document comprising the digitalwatermark such that associated payoff content is accessible through alinking service via optically capturing the portion of the linkedversion comprising the digital watermark.
 9. The system of claim 7,wherein the link engine is included in a linking service and the linkengine is further to, based on the at least one characteristicsatisfying the at least one evaluation metric and the selected typebeing an image fingerprint, create the linked version by linking animage fingerprint of the document in the linking service such thatassociated payoff content is accessible through the linking service viaoptically capturing an image of the document, wherein the linked versionis the acquired electronic document.
 10. The system of claim 7, wherein:the characteristic engine is to, based in part on the at least onecharacteristic not satisfying the at least one evaluation metric, decidewhether other characteristics of the content satisfy at least one otherevaluation metric for use of a non-prioritized type of machine-readablelink; and the link engine is to, based at least in part on the othercharacteristics satisfying the at least one other evaluation metric,create the linked version of the document using a machine-readable linkof the non-prioritized type embodied in the linked version and such thatassociated payoff content is accessible through the linking service viaoptically capturing the linked version of the document.
 11. The systemof claim 10, wherein: based on the selection parameter specifying apreference to choose based on popularity, the priority engine is toaccess link type popularity data of an analytics resource and prioritizethe most popular of the plurality of types of machine-readable link. 12.The system of claim 11, wherein: based on the selection parameterspecifying another preference, the priority engine is further toprioritize multiple of the types of machine-readable link and eliminateeach non-prioritized type of machine-readable link; and the plurality ofdifferent types of machine-readable link comprise at least one type ofbarcode, digital watermarking, and image fingerprinting.
 13. A methodcomprising: acquiring, with a network interface device, a messagerequesting that an electronic document included in the message beprinted; based at least in part on whether the document is atextual-type document or an image-type document, selecting, with aselection engine, one of an overt type and a covert type ofmachine-readable link for evaluation; deciding whether characteristicsof the content of the document satisfy at least one evaluation metricfor use of the selected type of machine-readable link; based on thecharacteristics satisfying the at least one evaluation metric, producinga first linked version of the document using a machine-readable link ofthe selected type embodied in the first linked version and such thatassociated payoff content is accessible through a linking service viaoptically capturing at least a portion of the first linked version; andproducing, based at least in part on the characteristics not satisfyingthe at least one evaluation metric, a second linked version of thedocument using a machine-readable link of the non-selected type embodiedin the second linked version; and making available, to a destinationprinting device via a computer network, the produced first or secondlinked version of the document in a print-ready format for thedestination printing device.
 14. The method of claim 13, wherein, whenthe selected type is an overt type of machine-readable link or digitalwatermarking, producing the first linked version comprises: adding theselected type of machine-readable link to the acquired electronicdocument to create the first linked version of the document.
 15. Themethod of claim 13, wherein the selected type is an overt type ofmachine-readable link, and the producing the second linked versionfurther comprises: determining whether other characteristics of thecontent satisfy a watermarking evaluation metric; based on the othercharacteristics not satisfying the watermarking evaluation metric,determining whether different characteristics of the content satisfy afingerprinting evaluation metric; and based in part on the differentcharacteristics satisfying the fingerprinting evaluation metric, linkingthe acquired electronic document in the linking service via an imagefingerprint of the acquired electronic document, wherein the acquiredelectronic document is the second linked version of the document.